| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 104 === Modern data centers offer huge aggregate bandwidth to clusters of tens of thousands of machines. However, because of limited port densities even in the highest-end switches, data center topologies typically consist of multi-rooted trees with many equal-cost paths between any given pair of hosts. Existing multipathing schemes usually rely on per-flow static hashing and does not differentiate between elephant and mice flows. As a result it does not fully utilize the available bandwidth due to hash collision among elephant flows. Further it also creates head-of-line blocking for mice flows in the egress port buffer. Multipath routing is a popular recent technique that protects data center networks from sudden congestion caused by load spikes or link failures. Multipath routing protocols however, require schemes for splitting traffic across multiple paths to achieve optimum bandwidth utilization. Current splitting schemes present a tussle between slicing granularity and available bandwidth utilization. Splitting traffic at the granularity of packets quickly and accurately assigns the desired traffic share to each path, but can reorder packets within a TCP flow, confusing TCP congestion control. On the other hand splitting traffic at the granularity of flows can readily resolve the packet reordering to support TCP congestion control but leads to hash collision among elephant flows, resulting poor available bandwidth utilization and increases overall flow completion time (FCT). In this work, we propose a simple yet effective multipath routing scheme that does not need elephant detection and uses the OpenFlow switches to implement a VLAN based routing to addresses the challenges of cost-effective scalability and a hard time-out based flow removal feature to break down elephant flows into mice flows and distribute them among all possible paths to achieve an efficient and dynamic traffic load balancing in data center networks. As per our simulation using mininet, we found a 44 % reduction in overall FCT and 32 % reduction in the consumption of overall flow table entry resources.
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